Ni, Pin;
Li, Yuming;
Zhu, Jiayi;
Peng, Junkun;
Dai, Zhenjin;
Li, Gangmin;
Bai, Xuming;
(2020)
Disease Diagnosis Prediction of EMR Based on BiGRL-Att-CapsNetwork Model.
In: Baru, Chaitanya and Huan, Jun and Khan, Latifur and Hu, Xiaohua and Ak, Ronay and Tian, Yuanyuan and Barga, Roger and Zaniolo, Carlo and Lee, Kisung and Ye, Yanfang Fanny, (eds.)
2019 IEEE International Conference on Big Data (Big Data).
(pp. pp. 6166-6168).
IEEE: Los Angeles, CA, USA.
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Abstract
Electronic Medical Records (EMR) carry a large number of diseases characteristics, history and other specific details of patients, which has great value for medical diagnosis. These data with diagnostic labels can help automated diagnostic assistant to predict disease diagnosis and provide a rapid diagnostic reference for doctors. In this study, we designed a BiGRU-Att-CapsNetwork model based on our proposed CMedBERT Chinese medical domain pre-trained language model to predict disease diagnosis in Chinese EMR. In the wide-ranging comparative experiments involving a real EMR dataset (SAHSU) and an academic evaluation task dataset (CCKS 2019), our model obtained competitive performance.
| Type: | Proceedings paper |
|---|---|
| Title: | Disease Diagnosis Prediction of EMR Based on BiGRL-Att-CapsNetwork Model |
| Event: | IEEE International Conference on Big Data |
| Location: | Los Angeles, CA |
| Dates: | 9 Dec 2019 - 12 Dec 2019 |
| ISBN-13: | 978-1-7281-0858-2 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/BigData47090.2019.9006331 |
| Publisher version: | https://doi.org/10.1109/BigData47090.2019.9006331 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Predictive models; Logic gates; Medical diagnostic imaging; Medical diagnosis; Diseases; Data models; Task analysis |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10159895 |
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